Hello friends, how are you doing? I am doing good. Thank you. Hey Richard, how's it going? Golden Dumpling. Hello. Hello Anthony. Yep, she fixed the email. Yep, I fixed the email. Hello. Is she delayed again? I'm fashionably late. Not delayed. But hello, Cypher. How are you doing? Hello. Okay, I'm going to turn my audio up a bit. Good morning, good evening, good afternoon. Hello everybody. How's everyone? What can we do today? We can do many things today. The day is full of potential. Where would you what can what are we doing today? Well, we are going to be covering essential AI skills for 2026. Who here is like ready for 2026? I think I am. I think I'm like very ready for 2026. Um yeah, I just am. Hello from Shanghai. Oh, hello. Hello from Hong Kong. Hello there. Me from Hong Kong. Me, too. I'm in Hong Kong right now. It's 2 a. m. in South Africa. Oh my god. Go to sleep. Come back. Um, come back for the replays. But thank you so much for being here. I do appreciate it a lot. Morning from Nigeria. Good morning. I want to be ready. Why are you not ready for is anybody okay? Who is ready for 2026? Put into the chat if you're ready. And if you can also write either put ready or not ready. I'm curious about people's readiness level. Do that while I open up the slides. Hello from Canada. Hello. I'm still in 2023. Yeah, true. I would like to be on 2023. 2023 would be nice if I get two years. Like three more years. Two more years. That would that would be great. Ready. You ready? Not ready. What means ready? Kind of ready. Just like ready for 2025 to be finished like concluded. Yes. Not ready. Okay. I think that should be good. Not ready. Ready for I don't know how to pronounce that word. Are the Italian dumplings? I don't know how to pronounce. Not ready. Ready. Okay. Well, you know what? Whether you like it or not, it's happening in 10 days. 11 days for me, 12 days for other people. Anyways, I stop rambling. Well, today we're going to be talking about the essential AI skills for 2026. Okay? Cuz going to 2026, it's actually really interesting in my opinion. There's um I feel like yeah like the AI world for the end of 2025 has been slowing down a little bit like we get like Gemini 3 release, we get a few other things. Uh but I think there are trends that are coming out which I think will be very interesting going into 2026. So that is what I'm going to be covering today. All right, let's go. Let us go. Okay, where's my slides? Too many tabs. Okay, perfect. Great. Okay. So, what we're going to cover today is why AI skills are non-negotiable these days. I don't think I need to convince you guys are here. Um, so four essential AI skill pillars, prompt engineering, AI coding tools that you need, AI agents, open-source. So, this is a this is one that I'm actually pretty excited to chat about. Open source AI, critical workplace skills, and then career impact and next steps. And then you know throughout the presentation talk I don't know what this is live stream please you know don't leave me just rambling about stuff talk to me ask questions please do okay so um the first thing is that I really hope you are all like convinced at this point that AI skills are really no longer optional in my opinion if you're a modern human that participates in society at this point if you don't have AI skills you're going to have problems s because most people should be at this level right now. Um, and I feel like there's like this unspoken expectation at this level in a lot of workplaces. Um, so if you don't, I do think that it will be hard for you to function um well in society and then just like be able to produce the things that you need to produce uh without AI. So I really think so. In fact, 81% of business leaders expect AI to be deeply integrated in their operations within 12 to 18 months. So that is fast. Three times productivity increase reported by developers using AI tools. 89% organizations already leveraging AI in some form. So really not surprising anymore. um to incorporate AI into pretty much every part of life uh like in terms of your work and own uh productivity as well. So what this means for you is that if you don't have AI skills, you are falling behind peers and productivity, missing out on career opportunity, struggling with repetitive tax and limited job market competitiveness. With AI skills, we can see that you'll be working three times faster on key task wage increase potential. We see a lot of job postings now do have that requirement of certain AI skills now. Um automating mundane work and then future proofing career trajectory as well. So um I do have some additional resources here which you guys can feel free to click in and just like understand things better and oh I right if you have not um signed up already like for our newsletter you can you will get this for free like um you I'll send you guys these things for free. So, please do so. I'mma pin the comment here. Yeah, pin the message. Um, so yeah, please sign up if you do want to get these slides. Oh, I'm going to like move my face because that's pretty annoying that my face is covering stuff there. Maybe that's better. Okay, great. Good. Let's see if anybody has any comments. Her live streams are always available. That is true. I thought you were going to give us an agent to track our finances. Did I ever say that? You gaslighting me? I don't think I ever told said I was going to give you an agent track your finances. Did I? I am into that right now though. Um I actually redoing I kind of redid my entire kind of investing strategy as well. Um but anyways, we can talk about that later. Uh right. Okay. So the four essential pillars of AI skills what in my humble opinion I believe that you absolutely need to know at this point um in 2026 would include um prompt engineering. So just this is like the defining career. This is the number one skill um defining careers is like literally the basics of everything. I'm going to be covering all this in a lot more detail as well. So [gasps] I'm going to go over them briefly. So uh prompt engineering so clear specific instructions AI context and constraint specifications iterative refinement and building prompt libraries. So really like the difference between good a good AI results and really great AI results do come down to the prompt these days. It's not really about the tool that you're using often times. It's just how it is that you're using it. And prompting is kind of like the language of AI. Um yeah it's like you can have a lot of different tools available to you but you don't know how to prompt correctly. you don't have that skill, then you're going to have um you're not going to be able to get the results that you want. So that's why it's like literally the most important skill. There's like a single skill that you want to master um is going to be prompt engineering. And then there's AI tool fluency. So mastering tools that transform different industries. I do think that there's like way too many tools. And I actually tend to not emphasize tools themselves that much, but I think if you have like a generalized chatbot that you like Chad Beauty, Claw, Gemini, Perplexity, you know, like general um tool that you like, it does cover a lot of things that you need that you would want to cover. But um if you do want to really like use AI um and really get the best results, there are like certain tool kits. I kind of call it like the toolkit of the modern human as well that you can choose to have like certain um AI tools that you use like for me I have like a certain stack of AI tools that I use on a day-to-day basis but this would be like AI writing content tools AI writing assistance like if you are someone who codes so cursor winer things like that and industry specific AI apps as well next is AI agents like this is undeniable the future of work is agentic AI in fact the now of work is also kind of mostly agentic AI now I think for like at this point if you haven't encountered agentic AI in some form already maybe you might not know it but I would be really surprised so it's really important to understand like agent capabilities building simple automation workflows like this is where um it doesn't sound like super sexy to be building automation workflows like agentic workflows but there's so much potential in this and there's so much that's coming out of it right now we're starting to like see the results of agentic AI um integrated into the workplace. Um agent orchestration basics and real world agent applications. So this is a shift from AI that suggests things to AI that actually does things autonomously. That's what AI agents are. And finally, responsible AI use critical thinking. So if you guys have any have used um say like Sora for example, right? like a lot of different um just this AI is very powerful and it has like a lot of things that will come out with but at the same time there is that other side of the other side of things where if you are not responsible and is using you can't understand like how to use AI properly I think it would also be really it would be really challenging for you so that's why it's important to be able to evaluate AI outputs for accuracy understanding bias and limitations um things like data privacy and security and ethical AI decisionmaking So the truth is that AI does make mistakes still and that is the case and your job is to be able to catch these mistakes and work with AI cuz in the end like AI is still a tool. It's not like a magical solution that's going to fix all your problems unfortunately. Um yeah unfortunately on that one. Yeah. So these are the four essential pillars of AI skills. See if anybody has any comments before I go into prompt engineering. Um, hi for Uruguay. Urg, I would like to know advanced rag blueprints and techniques. Abluma. Okay. Uh, we do talk about that in our agents sections. But if you have any like specific questions you want to ask me um about that, I can answer those questions about RAG specifically. But we do cover them as part of like we don't have like a rag specific thing but I do cover them in like our agents boot camp and things like that. So I'm happy to answer any specific questions that you might have. Can you just ask them to prompt themselves? No, you actually cannot themselves. Like it's still at this point you still need to give direction. And the problem isn't because like it can't prompt itself. The problem is that you can't if you can't articulate what it is that you want, how are you going to like that's the problem, right? Like it's not that like AI can't prompt itself. is that you need to articulate what it is that you wanted to prompt and that's like communication skills. Um just like how you communicate with humans, you need to learn how to communicate with AI as well. My company has taken THBT license and ask everyone in company to ask at least two questions every day to it can be anything. Yeah, I mean I'm not surprised. I think there is like an aggressive push towards that and it makes sense. It genuinely does. Um yeah, I think more and more companies are doing this and they probably will continue to do this as well. Oops. Okay, let me move my face a little bit. I feel like it's a little bit annoying. But there uh see where can we download the material. So I have it pinned over here. So if you click here, uh it's a mailing list and then I will email you all these resources like the Yeah, I I'll email you the slides after the workshop. I keep like changing the name. Live stream live stream. I've been teaching too many workshops recently. Yeah, but it uh just sign up there and you'll be good. Yep. The fear is real. Tina, hope that you would could explain more about AI agents. I still don't know where to start. Could you recommend? Yes. So, I will be covering AI agents um as part of this uh live stream in a bit. We'll be getting there. Thank you for your contributions to our learning and studies. Tina, thank you so much. Appreciate it. Oh, I thought you were on to context engineering over prompt engineering. I mean, prompt engineering context engineering. It's prompt engineering is kind of like context engineering is like the evolution of prompt engineering but in the end it's still about creating a good prompt right it's still creating either you're talking to AI directly you're using it as part of a gentic workflow it's still going to be about the prompt itself so I'm just going to call it prompt engineering just cuz that covers all kinds of prompting but yeah context engineering is just a form of prompt engineering but specific for building products and agents all right let us talk about mastering prompt engineering this is like the fundamental skill that you really need to do um is prompt engineering. So in 2026 prompt engineer is essential as writing a good email. Yeah, I really do believe that um you need to in order to be good at prompting you need to be specific. So vague prompts can get vague results. You need to iterate because in the end like you need to keep refining this output over and over again to make it better. And then building a library. So this one uh just saving prompts that work. Don't start from scratch each time. Like this is personally I have like a few templates like that I like to default to. Um and over time you like you start building up a good skill of how it is that you can prompt. So somebody asked earlier like can you get AI to prompt itself. What I generally do is like if I can figure out what are the key things I need in a prompt. I would actually put that into the prompt and then ask like something like Gemini chat beauty cloud whatever in order to amplify that like in order to um make it better as a promp. So you can do that, but then the beginning part of it, it's still really important um for you to actually have that base prompt. So this is the six part prompting framework that I like to use in terms of products. So um if you're just talking to CHPT, for example, like it's not you don't need to be as specific um as you do for this one, but I want to give you like a generalized prompting framework that does cover um this you can use for like different products for if you're building products. It can be like when you're building agents as well. So this is literally the six-part prompting framework that I recommend for building AI agents too. So I kind of want to give you this structure whenever you're trying to come up with a good prompt. So the first one is a role. Um you are describe the perspective expertise needed. Task is your main job is to whatever task it is that you want to accomplish. The input is I will give you blah like whatever it is you're going to give it. Output is you should respond with desired format style and structure. Constraint is never do certain things that you should not do. and reminders always remember to etc etc. So again this is kind of like over overkill if you are um just kind of prompting Chachi BT directly like this but generally speaking like if you are able to figure out what are the things that go into this prompting framework uh what like at least think through these things then you would have a much better result. So an example of here would be like writing a business email. So you're a professional business communication specialist draft follow-up email to a client after our first meeting input. I will give you just key discussion points for our meeting output. Respond with a polish email uh with professional greetings, meeting recap, blah blah. Clear next steps, friendly closing and constraint. Never use overly casual language, jargon with explanation or make promise I don't authorize. Reminder, keep tone warm or professional. Proof read for clarity and ensure action items that are uh action items are specific with deadlines. And I would also recommend putting some examples here as well if you it's if it's something that is going to be like writing a business email. So, uh I do have like entire videos dedicated to promp prompting like both for prompting in general and then also for prompting um for prompting for agents and products. So, there's like more frameworks that I do have. But I think if you're going to like remember a framework uh that would be pretty useful and you can start when if you're building your own products as well, it would be this one. Recommend you remember that. So, yeah. Um, so the pro tip here is that, you know, something like this framework template, you can just save it as a note or a doc and customize it for your different kinds of task. And this is the one that I like to personally use the most when I'm building products. Okay, so not going to go into too much more detail about prompting. Um I can as part of the resources I'll send you guys uh after this live stream I'll also send you guys like a couple videos that I have both on like prompt engineering in general as well as how to prompt like in terms of in the context of building products. How many of you guys are into building AI products or have already built an AI product? When I by AI product, I mean um anything that you're like anything related that you're building whether that's an agent or it's just like a AI product or it's LM app something like that. How many of you guys are building or interested in building a product? I am curious. Let me know in the comments in the chat. Uh, okay. From Gabriel, should prompts be tailored to each model to get the best results? Great question. I think when it comes to say if you're just chatting with a chatbot, I don't think it's really necessary to do that. Um, however, if it comes to building products, especially building agents, then there are certain things that you would tweak um depending on the model that you're using. Yes, I don't consider that to be like the most important thing. like the general prompt itself it's good enough can get you most of the results that you want. It's just that if you really want to go from like 80 like maybe like 90% to 95% or 95% to 98% then you might want to start tweaking it a little bit. It's not like the priority though totally into building trying to build building the infrastructure tried haven't gotten anything to work properly yet. Yes, that's why I'm here. I've tried to build but I'm failing. I want to build. Okay, great. Okay, let's and then feel free to ask questions about things that you're building specifically. Um, I'm happy to talk about that as well cuz I do think you should for anybody that wants to be building AI products at this point. You can quote me on this one. You know what? If anybody is interested in building things these days, you absolutely can and you should not be limited by not knowing how to code or something like that. You absolutely can at this point, which is kind of magical. Um, a integrated suspicious activity monitor in Python to start by learning the basics. Like what kind of product? Um, never monetize build some agents for myself. Maybe I should just follow a template. Okay, cool. Yeah, we can talk more about it, but I just think it's at this point if you are interested, um, I think there's a lot of things that you can building be building and it's pretty cool. Okay, so prompting. All right, guys remember prompting. Prompting is the number one fundamental skill. Okay, now let's talk about vibe coding. So building without code as I was saying earlier I think anybody that wants to build these days has the ability of building. So what is vibe coding? So this is a term coined by AI expert Andre Kaparthy basically saying that if you want to build things and you want to code right now you can just describe a natural language and AI can generate working app. No coding is actually required fully given to the vibes. He says embrace exponentials and forget that the code even exists. Um so in this new paradigm shift in which you are able to build things without code people who are designers right like you're able to become developers now like a designer can describe their vision in natural language and generate fully functional website um or application and hand off working code to developers. No back and forth is really needed anymore. Um I'll talk about like the role of developers in just a little bit. I'm not saying that it doesn't it isn't required but really vibe coding democratizes the ability to build and managers instead of when if you're a manager you're able to build prototypes now a product manager for example can build a working prototype to test ideas with users before investing in development you can validate concepts in hours not weeks entre entrepreneurs can build their MVPs now a founder with zero coding skills can launch a functional SAS product and I'm saying this like I literally know people who have done this right test it with your customers iterate based on feedback and monetize like single person like soloreneur being able to build an entire company uh like entire SAS product like this is very reasonable like I actually know like a lot of people when I say a lot like at least it's like I actually know a lot of people who are successfully doing this it's so possible now which it would have been impossible to do like no way you could have done something like this even like last year or the year before vibe coding tools and the large language models are good enough but you can Um and analysts you can do things like building dashboards. So business analysts can create custom data visualization dashboards without waiting for engineering resources. This is also like completely doable now. So here are like a couple different um vibe coding tools for nontechnical people that you can check out if you like. Um vibe coding isn't just about making everyone a developer. It's about democratizing creation. So nontechnical people can build, test and iterate ideas without depending on engineering teams. And this is kind of huge. Um, I was actually on a podcast yesterday. I don't know when the episode's going to come out and we kind of like talked about this in previous times. Developers held a lot of power uh in terms of just like getting started. Like it was like not knowing how to code was a massive stumbling block. Like it's a massive blocker to really building anything that is useful. But these days like it is not the case anymore. I think the role of developers is so important still because when you're using vibe coding tools, you get you can get to like a certain point, but if you really want to start scaling it um and making it into something that people can use, adding on custom features, you still do need developers. I'm not saying that you can just completely not have developers. I think you definitely still do need developers, but to get to like the 0 to 0. 5, 0 to 0. 75, you can do now just like even if you don't know how to code, it's pretty crazy. Um, I'm gonna see if there's any questions about this. Let's see. Prompt engineering sounds like a great idea for browser extension though. Yeah, it's the thing is like I think there's so many different prompt like prompt engineering tools that people use and stuff like that. Why is it that most people, you know, you can use them? But I think in the end the reason why prompt engineering is so important is that you can't really outsource that fundamental part because it's about communication. It's like having a human say you have like a human relationship. Can you outsource communication? No. You can outsource a lot of things. You can outsource implementation. Maybe you're like I want to buy I don't know something like you can't outsource the part in which you're communicating what you want to buy. Like that's what prompting is in the end. You're communicating with the AI. So you can make the communication better. you can amplify all these things, but without that base ability to communicate, um, you're going to have problems. So, like prompt engineering isn't something that you can skip out on, and I'm very adamant about that. Like trying to get AI to prompt for you without actually knowing how prompting works itself, like you're not going to be able to get the best results, especially when you start building products. Um, and then, you know, start building products and having to test things and evaluate things and then you're like iteratively changing things and tweaking things like with vibe coding. It's really hard for you to do that without a good basis of prompting. Hi Tina, I just joined. Welcome. Is there a website you're showing the main resource we'll be using in the live stream? Yeah. So if you look at the pin comment, you can click over there. I'll be sending you to slides afterwards. That's what I'm going to be using. So limits is equal to scalability and safety. Uh what are the limits of VI coding? Great question. So when it comes to a non-developer right I think you can get to like as I was saying earlier 0 to 0. 5 0. 75 even the limitations is when you want to start scaling it is where I would put it like um let's say like scaling it to more people like in the few thousands of people you can get away with but like perhaps like more than that um yeah I would say like when you're getting to actual having like users and trying to scale it that's a limitation and another limitation is going to be if you're trying to add features So vibe coding um you can get to a point in which you know you have your core features and it you know assuming they're not like very obscure features you can probably get it to work but if you're trying to add like additional features to it that is more advanced that's going to be more niche custom then you're going to start running into more difficulty if you're vibe coding with um with a non-developer like completely with no code right I think I think that's kind of where the limitation is going to lie and also most of these vibe coding tools um these non-developer centric vibe coding tools are going to be web- based. So if you're going to I think there's you know they're ruling on the mobile side of things as well. But if you're trying to um do like mobile apps, if you're trying to vibe code things that are not web- based, for example, that's going to be very hard uh to do with just completely no code tools. Uh I halfway through the presentation. Can you share a copy? Yep. Check out the link. Repl is amazing. I agree as well. There's a lot of different vibe coding tools and I think a lot of them there's like different differences between them. Um so that's why like I said I tend to not focus so much on the tools themselves because I do think like there are certain tools like for example like right now my go-to tool has been using Bolt. I think it's like one of the best ones for just like getting everything started. Um but you know you can make an argument for a lot of the different other vibe coding tools as well. I think it's more like a skill thing like choose a tool that you think vibes with you and makes sense for you. Um, and it's more it's also specific to the product you're trying to build, right? Like certain tools have certain stacks that is more useful for um that specific thing that you're building versus another. But really in the end, I think it comes down to skill and what is like with vibe coding, you're using prompting, right? That's literally what it is that you're doing using prompting. You develop things like a PRP um which is a prompt requirements. Oh my god. Product requirements prompt. So it's like a uh like defining what the product is. All of that is prompting in the end. Okay. So then for on the developer side, so once you get to like 0. 5, 0. 75, it's still really important for you to then pass it on to a developer. And for developers, you know, if you are a developer already, if you're not using AI assisted coding, um I I'm not really sure what to say at this point because like I do think there's so much like coding tools like coding agents that developers can use. I do think this is one of the areas that has seen the most amount of success when it comes to using AI tools is for coding. So to developers, AI assistant. So for developers, AI isn't replacing coding, it's augmenting the workflow. So, think of it as like an intelligent pair programmer that understands your codebase and guides you to solutions faster. Like right now, like whenever I want to go code something and I'm able to do it so much faster, like crazy, so much faster than when I was trying to just code myself before. I like I don't know if I could even go back to that at that point. It's just having unlocked the ability to just code so much faster now. Um, so yeah, like you don't even do things like checking Stack Overflow anymore. or like you literally have an AI assistant that can help you with coding. Previously, you got to do things like searching Stack Overflow uh for solutions, copy pasting code snippets, adapting to your specific use case, reading a bunch of documentations um and then not knowing how to do that, debugging, trial and error, repeating for each problem. So, this is like super timeconuming context switching heavy situation. The old way like most of the time when you're actually developing like when you're like coding something, you're not actually like writing code, you're searching stuff or trying to fix stuff. But now um using AI you can describe what you need in cont in context generating tailored code review and guiding refinement AI running test automatically and iterating until perfect. Um it's really fast it's contextual it's conversational and on top of that it's just like you still have like a lot of control compared to Oops. Uh I don't know what happened there. Okay. you still have a lot of control compared to just a pure vibe coding tool where like you're going from a no code perspective, right? But with code with AI agents that help you with code um as a developer AI assisted coding, you have that control, but you're just able to do so much more and so much faster. So yeah, you can do a lot of these things. Context aware code generation, intelligent debugging, automating tests, refactoring and optimization, document generation, multifile editing. Uh there's just so much. And here's like a few examples again like different ones. Yeah, not going to go into too much detail about the tools themselves. Um, but just choosing one of these AI assisted coding tools, they really would help so much when you're coding. So the reality is that there's a 300% productivity boost. Developers using AI assistance report completing task three times faster. You're not learning to vibe, you're learning to guide, refine, and validate AI generated code through an iterative conversational workflow. So bottom line is that if you are a developer, AI assisted coding doesn't actually replace your skills. It really amplifies them. You will still need to understand uh the code architecture and debugging, but AIS can handle the repetitive work for you while you focus on solving the hard problems. So if you are a developer, this is absolutely a skill that you need to know uh in my opinion, in my humble opinion in 2026. Any questions? Can you put into the chat um you guys? Are you a developer or are you a builder? Let's say like builder is like no code people. Um and developer is for people who are technical developer or builder. Put it into chat. I'm curious. So basically we got to invest in self-articulating thought through thought into propositions. Yes. Reading skills right now is low. Yes, I agree. um got to invest in self-articulating thought into propositions. Yes. Is like that's what prompting is. You're like articulating yourself. That is true. What's your favorite one uh in terms of AI assisted coding tool? So for again not so much focus on the tools themselves, but the one I'm currently using most is Warp. Um yeah, I am using Warp. The other there's like a lot of different popular ones as well. It's again like choosing one that you find that works well for you and works well for your codebase as well. So if you're using something like Python, you would be fine with most of these, right? But if you're using something that's a little bit more niche, um I don't know like for example like goodo for example, right? If you're doing like game development, then you might want to choose like a more specific one specific for that. And then a lot of like people also you can like switch out different models as well um while you're using AI assisted coding. So you can find one that works well for your workflow. Just got here. Hello, welcome. Okay, so vibe coding is cool. However, you still need to understand the code because sometimes AI does not get it right. Exactly. So you get to that 0 75. 5 to 0 75 of your product. Then you do need to switch to coding. Like you still need that final step. Developer builder I do both. Nice. Dev builder dev builder dev. Oh, okay. Good mixture that we have here. Very nice. Developer. What is best for absolute beginners with no code knowledge? So on the builder side like previously over here uh these are some of the ones that are the best to begin with in my opinion. Um if you want to start off yeah [snorts] there's also like replet uh if you want to try that. Firebase studio is the free version. So for those of you who do want to try something without paying right now there's fire studio and then there's also um like open source tools as well like metagp for example. So I don't have that here. I'll talk about open source a little bit later but there is like increase in open source tools and five coding tools as well. So those are all ones that you can try out a lot of different out. All right now let's talk about AI agents. This is I would say okay like any modern normal like person like needs to know prompting and needs to know like different tools and stuff and if you're a builder um if you want to build stuff where you're a developer I do think you need to know like vibe coding for builders AI assisted coding for developers. Now for people who I think agents is also really important for people who do want to take that step um and actually start building products right like in the end like with large language model like products the kind of golden standard the thing that you're aiming for is building something that's a that's something that's an agent something that's autonomous um and this is also where there is a lot of opportunity for impact in the business world so what are agents let's first define that so agents are software systems that use AI to autonomously pursue goals and complete multicept task on behalf of users with minimal human insight oversight. Sorry, not insight. You didn't need human insight without with minimal human oversight. The key difference is that traditional AI, if you're just talking to like a chatbot, for example, is able to respond to the prompts um and will like tell you stuff, but agents can take action. It's able to do stuff like make decisions, use tools, and work independently to achieve objectives. So, um we're moving from chat bots to building autonomous agents. So traditional AI like chatbt, you're just kind of talking to it. You're waiting for a prompt. You're responding to a question. There's no like actual follow-up action per se, and you're not using tools independent. You can't use the tools independently. Um, it also requires a human for each step. For example, if you're talking to chat to BT, you would just do something like, oh, write me an email, generate this text, and then you like copy paste it into your Gmail, which is great. You know, that's very useful. But when it comes to agents, agents are able to initiate tasks autonomously. You can complete multi-step workflows, use tools and APIs, make decisions independently, and it will report back to you when it's complete. An example of an agentic workflow would be you can ask a question like send a follow-up to John. Um your agent will figure out like goes through your emails, figure out what it is that you're talking about, who is John, right? Which followup. It will find the email, draft the response, schedule the thing, and then also confirms it after being sent. So I hope you can see the difference between just using a chatbot um versus building an auton autonomous agent to do it. So here are some examples of real world agent applications. Customer ser customer support agents. So these are agents that can handle tickets and to end um reads inquiry searches knowledge bases draft response and escalates if needed and follows up. The result is that you're going to get 65% reduction in support tickets is based on chatbase. Um there's also like sales research agents. These are agents that are able to research prospects, find contact info, analyze company data, draft personalized outreach, and schedule follow-up. So, you can see like the results are here, right? You can literally see the results in the business world now. And it's impactful. For example, we can see from Lumen that there's four hours saved per seller weekly, which is huge. 4 hours per seller. Um, data analysis agents are able to pull data from multiple sources, clean it, run analysis, generate visualizations, create reports, and distribute to stakeholders. So result is that your weekly reports are going to be previously which was taking hours, it's only going to be taking minutes. Now another example is H is HR onboarding agent. So it's able to do stuff like create an account, send a welcome email, schedule meetings, assign training, track completion and follow up of missing items. So this will result in much more consistent onboarding with zero manual work. Um so these are all agents that people have built and they're seeing real results in the workplace already. So what I think you need to know about agents if you're interested in building them is first of all understanding how they work uh when to use them including workflow design like how it is that you can break them into different tasks tool integration integrating and testing and validation this is really important and then also monitoring so I'm going over this really fast right now I also know that but I just kind of want to give you guys kind of the basics of here's the things that you do need to know when we're building agents like we have an entire 28day boot camp where we go into this in a lot more detail but so I'd definitely don't have time to uh talk through all of it right now, but I do want to tell you like these are the things that you need to learn if you are if you do want to go explore this yourself. So with agents still it is still important to understand that it's not a magic solution. Agents still need clear instructions and guardrails. So back to the prompting situation, right? And guardrails uh knowing what it is that it should or shouldn't do, error handling, so planning for failure and edge cases. It still needs human oversight. Um, and the way that you want to do that, you want to start simple and you still need iteration over time. So, I really think that agents represent such a massive opportunity. Um, because there's actually a lot of like AI solutions that people would build right now, but like where like for example, we do B2B consulting and we build B2B like AI solutions for companies, right? I actually think where a lot of value lies going into 2026 is not necessarily like building like an entire AI agent as a full solution these days. It's more about helping companies integrate agentic workflows like more custom agentic workflows into their current workflows. Like for example, if you're building if you want to like get an agent to help you, I don't know, uh, report generation, right? Let's just say like data analysis agent, like you want to do that. You want to automate some of that very manual process. You can't really just tell the company, hey, like change your entire workflow. That's probably not going to happen. Um, that's why like out of the box solutions also aren't the best. So generally what they need to do and this is what we get hired to do is that we would help them figure out what like building a custom agentic solution that's able to fit into their current data pipelines their current like data analysis pipelines to be able to come up with that final report um and distribute that. So there's a lot of value there's a lot of impact that lies in this area. It's like almost like that glue like you're connecting together agentic solutions and building custom solutions for existing companies. Um so this is where like I also really recommend people who are interested in building agents to start like thinking about freelancing. U if it's for your own company like think about how it is that you can integrate agents into existing workflows as well. Anyways, I'm going to stop rambling. So I do think there's a lot of potential here like massive potential here. Um potentially for people who want to be like freelancers, start agencies and stuff. Uh a lot of companies are looking for this kind of work and I know this because that's what we do. Um okay so getting started well so you don't actually need to build agents from scratch which is wonderful. You can start by understanding agent workflows and you can explore no code platforms like NA10 make zap year to create simple agents. Isn't that pretty cool? Like you can literally create simple agents now using no code tools as well. Um yeah we have a boot camp that covers agent development in depth from planning to production to deployment. So even like within our boot camp like we offer two tracks, right? One of them is a no code and a code track. Um and the reason why we do this is again like I don't like to actually focus so much on the tools themselves because they keep changing and getting better over time. But if you understand how agents work, what what's the structure of agent, what's the infrastructure, what are the actual basics required, you can actually use different tools to build the agent. The tool itself is simply just a tool. Okay, enough rambling about agents before I go into open source. Any questions about agents? I hope you guys have questions about agents. Let me drink some water first. Do you think Gemini has better data analysis capabilities in chatbt? Um, in some ways, yes, in some things that you do. Me personally, I actually still much prefer Claude for like data specifically. Anything that's more technical that cries analysis, I tend to go with Claude, but Gemini is really good. So is Chachet as well. I think Gemini might be a bit better than Chacht. Don't quote me on that one cuz I think it, you know, they're similar, but I personally think Claude is the best right now in my opinion. Um, let's see. Ra like rather than the sort of step-to-step execution like any intent sequences or even something hyper sophisticated like do a thing and it does all the things to do the thing. Okay, I think that was a response to somebody else. Cool. Um what's the cost of your boot camp please? Our boot camp is 997. Yes, 997. If you go to attend some of our if you have gone to some workshops um then you do get a discount as well but the base price is 997. We do not currently have a boot camp available. Um we're I think we're launching again early next year. So you can also sign up for the weight list if you want uh to get more information. So all of our like workshops and things like that because I don't like spamming YouTube um about this. So that's why we have like a mailing list where if you're interested, we send out information about um when that we open enrollment and things like that. Are you drinking directly out of a vase? Excellent question. Yeah, I am. Not a vase. Is it is a water jug? Is that better? I know, right? Um talk about AI job marketing for people who get certifications. I'm not sure if I'll earn a living or if it's just for fun. You know, hold that question. I do want to talk about that. I do think careers uh in the job market is very interesting to me. If you ask me that, can you ask me that question a little bit later? I want to get through the slides first. Um I'm actually Yeah, I think that one's interesting. Boot camp with them worth it? I hope. Is that a statement? If it is, thank you very much. Oh, hey. Yes, it is a statement. You went through a boot camp. Hello. Um thank you. I'm very happy to hear that. Okay, I agree. I love cloud data analysis agents are sus. Bad data is worse than no data. And most companies set up semantic models and write reports and dashboards unless something like analyzing unstructured data. I think that's the thing. There's actually a lot of um a lot of it is unstructured data. And by unstructured data, what we're referring to here is stuff that's like, you know, people maybe going on interviews and saying things, uh sending emails like kind of like written. Oh my god. natural language like unstructured data as opposed to numerical data. I think agents are amazing for that and a lot of companies can get so much insight by incorporating unstructured data into their complete analysis. Even with structured data, uh I think that combination you can get really good results from it. Even like with our own company like when we do our analysis with you know our internal products and like whatever things like that um yeah like when we're we you know whenever we do like an audit um and look at the data and then also analyze the data yeah we get a lot of really amazing insights um from that. All right talk about open source now. [sighs and gasps] Okay, this one is kind of like kind of it kind of came out of left field for me. Maybe some of you guys in the chat like if you can if you saw this coming like please do put in the chat because I'm first to admit here that I kind of saw like oh open source is really cool and stuff but I did not expect how quickly open source is rising. I'm actually kind of shocked that nobody's really talking about it yet on the internet. So I don't know maybe we're going to get like more internet people talking about it um soon. But yeah, this one kind of like came out of left field for me. I just didn't see it being so fast. We can see that with open-source AI. Um the performance gap is very much closing now. So gap is narrow from 15 to 20 points to 7 to n points parody expected in Q2 2026. This is from a benchmark analysis. Oh um yeah. So I'm before like I agree with that. So with open source like what I mean by that um is models that you're able to use and tweak and download and do stuff with without having to go through like a company. So whenever we think about very popular ones like uh let's see like Chad GPT cloud Gemini like these are all closed source AI. So in order to access these models, you have to go through their platform. You have to use their APIs and like build on their infrastructure. And it's also more of a black box because we don't really know what exactly it is that they're doing to their models, right? In in the back end. Um but with open- source, this is in contrast to that. These are models that you can actually use. They're available. Often times they're really cheap or free completely and you can use them build on top of them. There's a community You can develop them, put them into different products, fine-tune them as you like. Um but these are called like open source models and the most popular open source model these days is deepseek for example. So that's what I mean by open source. Yeah. And then another like super interesting thing is that open the open source AI movement is being led by China. Like I think that's super interesting because I think western AI has been very much like concentrated um has al has like very much been closed source AI, right? well from China is like just kind of just like rising up and I didn't really expect this at all but Chinese open source like starting with Deep Seek like Gwen like a lot of these um Chinese models are open source they're really cheap were free um and that's why like tools that are built on top of them is also free were a lot cheaper and uh I read the stat recently I think it was A16Z that said that um now 80% of the companies that are pitching to them are building products using open-source. Like they're building products on top of open source AI. That's super interesting. This is like a really big difference than just like a few months ago when the majority of people were still using closed source AI. And that's because open source AI has gotten so much better and you still get the benefits of open source of it being cheap, you know, being able to tweak it, do a lot more things to it. So people have just really like switched over to using open source um when they're building stuff in particular. Yeah. So you get like 3. 5 times cost savings compared to proprietary models. Um 11 times year-over-year growth in tech industry AI adoption. So industry adoption exposure there's a lot of it in technology, healthcare, manufacturing. It's also really useful for things like healthcare for example because um you generally like you I don't know like most cases you don't want to be uploading patient data into like a closed source AI like Chacht for example directly because you don't know what's going to happen to it, right? But with open source like you have that model so you know where that data is going build an infrastructure and privacy around it. So this will allow you to still abide by healthcare regulations and building healthcare products. So this is like a huge innovation that is opening up a lot of these um industries that previously were constrained because of privacy and regulation concerns. Yeah. Uh and manufacturing as well. So I'm going to stop here for now. So yeah, like I think there's a lot more about open source I'm really interested in covering. And also starting in 2026, our AI agent boot camp, we're going to be covering open source AI deployment, finetuning, and production as well because I think this is absolutely crucial. It's like a huge thing. It's just going to start exploding more in um 2026. So definitely check that out if you want. Let me see if anybody has any questions about open source. Whoopsies. Oh no. How do I get myself? Whoops. Why can I not see comments? Too many tabs open. Okay, cool. Let's see. Comments. Should one be concerned with security issues using China origin AI etc or open source? So that's why it's open source, right? Because um I think China knows that a lot of people are not going to be cool with using their Chinese servers. That's why they're developing on the open source side. You're not using Chinese servers, right? You're running these Chinese models on your own servers. You can do it locally. on the web um on the cloud or whatever. So you're just simply using the models that are being developed by China. So that's why like no, you should not you don't need to be concerned about security issues because you actually have way more control of the security with open source than you do with closed source because you don't really know what open AI is doing, right? Um what does China do with your prompts though? Security risk enterprises. They're not doing anything with your prompts because again you're taking the models and doing the stuff that you want to do yourself. So you're not like sending information back to the companies themselves. You're just using the models and tweaking it and developing it. Um, oh, thank you so much, Rex. Yes, if you are interested in the boot camp, um, if you want, Rex has put the link on there. We do have a boot camp that should be coming up early in 2026. So, last time, and thank you guys so much for this, like we sold out under like a couple hours, and prior to that, we sold out under 1 hour, I think. Um, so we only we do limit it to 100 spots because we want to make sure everybody gets the best experience possible and we do sell to the weight list first and we've consistently like sold out through the weight list. So if you are interested sign up, please sign up for the weight list so you can get more information about that and you that's also how we're going to be sending you out information about uh shorter workshops that we do as well. Like the app sprint workshop is when we built applications in an hour and a half. We had an agent breakthrough. like starting it's like a mini agent workshop that we did a couple weeks ago. We had a freelancing workshop as well. Probably going to have an open source workshop um for next year too. So that's where we're going to communicate these workshop things. Um okay let's see open source sounds like how Python was able to become so widespread. People can build commercial products on top of open source. Exactly. This is exactly what it is. There's like the parallel is very clear here. Um it's like there was a time in which you know people were using proprietary coding languages right like what was popular was not like JavaScript or like Python it was like propriety languages that are being developed within companies um but then the open source movement came and then there was a lot more um interest in stuff like Python because you can it's a community- based thing and everybody had access to it and then it was free to use and then um yeah over time now the common thing that people do is using open source developing like coding languages, not like proprietary ones anymore. Like when you're going to learn coding, you're learning like Python or JavaScript or something like that. You're not learning like I don't know I don't even know what the names are. I can't even think of the names because they're like proprietary. It completely just like died off. Um and I feel like this is seems to be a trend that may be repeating on the AI side of things as well. Just the open source side. um building things out in the open, having a much cheaper, having a lot more control, community involvement, fine-tuning. That would be really cool. That seems to be the trend um that we're moving towards now. Um essential AI skills as a servant. Well, essential AI skills in my opinion, like let me put that as a qualifier. In my opinion, these are the things that you should be learning. Yes. Um yes. Yes, agent breakthrough was great. Thank you. Thank you very much. I'm really really glad that you thought it was great. It's helpful. Um thank you guys for our past students. Thank you so much for sharing your experiences. Um we're really happy about that. We spent a lot of effort like genuinely in making the workshops and boot camps and things like that. So that it is making me really happy right now. Anyways, okay. So um does it matter which model is better? Does the model [clears throat] you use do what you want matters? That is true. So questions, [gasps] do we know the start date for the early 2026 boot camp? We do not currently know. We know it's going to be in Q1, but we don't exactly know the date yet. So I don't want to like say something incorrect. Yes, but we will announce it as soon as we do know the date. Um what open source was open source boosted by deepseek or were there already talks in industry about building things out in the open? Yeah. So there was definitely talks and I think again like I don't know what was going on the mind of these model developers. Um I think probably perhaps what happened was uh there was like open source that was already brewing but it was just sort of you know it was just like nowhere near as good as a closed source model. So people weren't really paying attention to it as much. But when DeepC came out, that was the first time when people saw like, oh my god, like a open- source model that is way cheaper, has all this control, no like none of those privacy concerns and whatnot, is able to perform on par close source AI. I think that was like the breaking point. And then after that, it was a flood of open source that started coming out um primarily led by Chinese AI um Chinese AI companies for these open source models. And then people started developing tools on top of the open source models. So they were able to make it so much cheaper than the closed source equivalent, right? Because closed source if you're developing on closed source models then you have to pay the premium for using those closed source prices. So then you know when you're selling these products you have to also mark it up higher. But for people who are using open source models on top of the other benefits that we talked about um you're also just able to make it a lot cheaper for people um because you're paying less for the models themselves. So the cost overall is also a lot cheaper. So yeah, that kind of opened up the floodgates uh in terms of the open source movement and it happened really quickly just like within the past few months. Yep. Have how many of you guys have tried out open source? Can you put into the comments if you have tried out open source models before or open source products? Put in the chat. Okay. Oh no. Okay, let me go to through the size a little bit faster. I got excited. Okay, so let's talk about critical workplace AI skills. So again, in my opinion, these are the things that you do need to know outside of just the technical side of things, right? Data literacy, I think, is super important. Still understanding data itself is non-negotiable. Being able to read and interpret data insights, identify trends and anomalies, check for errors and biases, making data informed decisions because with good data is really the basics, the basis of how you're developing products and on AI as well. AI is built on top of data. So that's why it's important to have data literacy, critical thinking, don't have AI outputs blindly. I'm just going to put that here. Uh because so many people are using AI these days and there's always like that other side of the equation where people might be using AI in ways that maybe are not the best ways. And it's important for you to be able to distinguish between what is a good way of using AI, what is not and looking at the outputs like is this AI, is it not AI generated, is this actually real? You know, all of these questions. Um AI is powerful but not infalluable. So is quality control, continuous learning. So if there's like a singular skill like meta skill that I think has been the most beneficial to my life by far is just the ability to learn. Especially now with the AI landscape, it's changing so quickly. There's so much development. I was talking about the open source thing. This is happening like just a few months ago. you know when it meteoric rise and 80% apparently of companies that are like startups are building off open source now like this literally happened within the span of like months and the AI landscape itself is changing so quickly as well so being able to learn is like that superpower like that you the modern superpower is your ability to learn and workflow integration so knowing when and how to use AI this is so important like when people are building products like we've found that people who go through our boot camps for example, right? Like there's people who go through our boot camps, build agents, um, and then like sell them and things like that. And what's interesting is like the people who are able to build like the most impactful products, like the ones that they can sell, the really great ones, they're actually ones who really understand when and how to use the AI. like they're actually people who have understanding of um enterprises like understanding of the business side of things and what they're building and then combining that with knowing what AI is good at and what it's not good at to build really good solutions. So that combination is where it's at. So you need to be able to identify automation opportunities, integrate AI into daily tasks, balancing AI uses human expertise and optimizing processes continuously. So understanding that you can use AI to eliminate grunt work, not to replace thinking. So yeah, like this is also a really big one. So in my opinion, these are the critical things that are not technical in nature, but they are really important as we're moving in 2026. So technical skills can get you into door. These workplace skills will let you be able to lead, innovate, and advance your career faster than those who only focus on tools themselves. Okay, so career impact, talk a little bit about this. So AR skills are the new career currency. Like I don't know if anybody wants to argue with me about that one, but we can do that if you want. I think is quite clear in every industry professionals with AI skills are becoming indispensable. They're not just keeping up. They're leading transformation of how things are going out. So if you need AI skills in order to stand out like while others are waiting around, you're the one that you can be mastering the tools that defining the future of work. Um using AI can just make you so much more productive. So it will lead to faster promotions, better opportunities, higher earning potential, all within reach. Especially if you're working at a company, if you can integrate AI solutions into their company, there's like so many hang lowhanging fruit now. Um, building something like that, you can like significantly save the money or increase output and just do things that you weren't able to do before. Um, yeah, like stuff like customer service stuff, uh, analysis, automation, like report generation. These are all like very common like lowhanging fruit that a lot of companies deal with. So, there's actually like solutions that you can build and people know about these solutions. It's not like it's rocket science here, but if you build it and custom for specific types of companies, then they would be able to reap those benefits. Um, creating like being able to create build ideas that are impossible for launching projects that you just simply could not have at all. Like if you want to be an entrepreneur, a solarreneur, there is no better time to do this right now. You can literally build products from scratch, like whatever it is that you want to build so quickly and at such low cost. Um there has never been a time that you are able to do this. The number of like soloreneurs that I know like people who are lifestyle um soloreneurs you know like freelancers uh who have agencies. Yeah. It's just massive. Like there's so many people doing this and they're like doing really well doing this because they understand how to use these um these skills and future proofing as well. As AI is continuing to reshape industries, you're going to be ready like you're not just scrambling to catch up. it is very much the way where things are headed. Um, yeah, AI is is the future and it's already here. So, if you don't know these skills, it's going to be difficult for you. I would me personally like you there's like pros and cons to everything, right? Me personally with the technology this powerful that's here, I would much rather be the one that is defining how it's being used as opposed to scrambling to catch up to it. Okay. So, I think the most costly mistake is not starting now. Um, so every day you delay the gap widens. The professionals learning I today will be the leaders of tomorrow. And I do not doubt that at all. I will defend this one. All right. Open floor. Okay. Sorry, I kind of went over a little bit. Feel free to drop anybody that needs to. Um, but I'll stay around for a little bit longer. We can chat about the things I just talked about in the slides. And also if you have any additional questions, we ask me anything when we talk about like learning questions, career questions, tool questions, whatever you want to ask. Please feel free to do so. Um, let me go back to the chat. Does this page designed by AI? Yes. So, all these slides are also designed by AI. They're designed by AI and they're executed with AI as well. Yes. Nice icon graded. Oh, thank you very much. [gasps] Thank you to our wonderful team. Uh, yeah. So, Ibrahim from our team, which he's also a um I don't know if he's here right now, but shout out to Ibrahim. He is our instructor. Uh he made a he made a internal app that's able to produce these um slides. Well, previously it would have taken forever to make these slides. [sighs] Yep. To use open source, do you need a lot of personal comput? Nope, you don't need to do that. You can also run things on the cloud as well. So you don't need a lot of personal compute. Uh do we need a good understanding of maths and Python to learn AI? Nope, you do not. Do you still offer the vault to the folks in the wait list? That's what I purchased and was just as good as live stream. There are follow-up meetings to ask questions worth every dollar. Do we still offer the vault? I do not believe we've been offering a vault for the past few cohorts. No, I do not believe we are going to be we had offered them. That's actually really good feedback though. We I think we actually stopped offering devolve because we thought that people were not getting as much out of it um as we wanted to. But thank you for that. We can maybe re-evaluate that. Um let's see. How often do you live stream? I just randomly found the stream in real time after your video is recommended by YouTube. Oh, that's a good question. I stream usually like once a month, I would say. Um, perhaps more. If there's like something really exciting I want to talk about, then I will stream more often. Sometimes a little bit less, but I feel like kind of now once a month. Yeah, plus or minus one or two. Um, ah, so many questions. Thank you. What's your favorite color? Wow, I'm stumped. I don't know. What's my favorite color? Yellow. Maybe it's cuz my last name is yellow, but favorite colors. Yeah, I guess I like yellow. Um would love to see it. The slide the slide app. Yeah, maybe I'll show we'll we can like I will demo it at some point. Not now, right now, but because there's like proprietary information in it. Yeah, maybe we'll demo. I think you're referring to like the slide to make how like how it is to make the slides, right? How we make the slides. Yes. Maybe we'll demo it sometime. That's an example, right, of like an app, an internal app that we use that dramatically changes like our um it increases output so much. Like our team is actually really small. Uh the fact that we're able to like do these live streams, like create content, that we're able to like make um run these boot camps and like workshops and stuff. Yeah, it's pretty crazy. Purple. That's true. Well, purple is one of my favorite colors, too. Purple is complimentary to yellow, but I do I'm surprised it's not purple. Purple is like octopus purple. Yes, octopus purple. My favorite color is yellow. Octopus blue. Um okay let me see if you use open source where's the data stored compared to non-opensource if that makes sense. Yes. So you can store your data in databases that you're controlling. So you can store it you can have it locally but on the cloud. So you can store it like you know wherever it is that you want to store it. You have like your own servers like on prem. Um if you're a company you care a lot about having a lot of privacy control. Um so it yeah you can store in a lot of different places and then you can just connect your data storage to the application that you're building with the open source large language model for example with like closed source um you can it's usually the data that's stored there are ways of doing it outside of the ecosystem that you're building on top of but generally speaking like with for example if you're going to use like chat GPT right like open AI stuff and you're using like GPT models then the data you they do have like databases that you can connect to as So they have like a full ecosystem of this, but you can also have your date your data stored in different places too. So it's not necessarily that um you need to like store your data in a specific place. You can just store it where you like and then have access to that with your model. I hope that makes sense. But with open source, you generally have more flexibility on how it is that you're storing it and where as well. Um, do you have a guide on how to build a platform on top of an open source model? That is a workshop idea that I think we're going to do beginning of next year. Yes. Not yet, but yes, I think so. What do you think about the field of AI safety? I'm so glad that you said that. I did a video about AI safety and it was like the worst performing video I had done in like 3 years. I was kind of sad about that cuz I thought it was a really important video. So, I was like, darn it. Um, I'm really glad that you asked that. I think AI safety is one of those things that's like super slept on and then something's gonna happen big at some point. Everybody's gonna go, "Oh my god, AI safety. " And then we're going to have like a huge influx of um, attention on AI safety. But it's a field that's like inevitably going to grow even more. Um, knock on nothing like terrible happens, but it's just like we're like kind of just like waiting for a disaster. Knock on wood, but like I were kind of like waiting for a disaster to happen right now for people to really pay attention to it. While really like it's something that you should really be paying attention to. Uh for people who are interested in AI safety, I think that's a field that is very ripe for a lot of opportunities. Uh [sighs and gasps] let's see. Have you ever had a shirt moment during a live what? I don't understand the question. I'm learning AI by myself, but I'm not sure in which situation to use it because I'm not sure whether potential customers even know what they that they need it. Take into account take that into uh take into account that I'll be freelancing. So, okay, that's a great question. You should not be thinking about whether your potential customers think that they should or should not know whether you want to use AI in a situation. That's not their job. That's your job to figure out where it is that you should be using AI. What it is that you're freelancing for is solving a customer's problem. Like you're not being like, hey, you should use you should incorporate AI into company. What you're selling, you know, selling if you're freelancing would be like, I can solve your problem. Let me solve your problem. And then the way that you solve the problem is going to be through AI. Does that make sense? You're not a like you're not advocating for the use of AI purely because you think a company should use AI. you're just offering a solution in general, but your solution happens to be AI. Um, how do you sell an AI workflow? I guess that's kind of related question, kind of similar to what I talked about. There's different ways of doing it. You can build like a product like a AI solution and try to sell that. Um, like you can build like a vibe coding tool that's like a AI solution for example, right? Like a full AI product and sell it. You can also do freelancing. Um, and you can also where you're like working with a company and building up custom workflows for them. So that's what we do as a company. We can also do consulting as well, which is something that we also do. We don't build the products themselves, but we kind of like help companies incorporate AI into their existing workflows. Yes. Makes sense. Wonderful. Great. All right. I'm going to leave it as that because we are a little bit over already. Thank you so much for joining this live stream. I really hope this was helpful for you. Um yeah, you moving into 2026. So you guys got a few days to plan out what it is that you're going to be learning for the um for 2026. And I hope this is these are the skills that you're going to be learning then. And again, if you want to get the resources like the slides and stuff, just you can sign up on the pinned comment. Uh it's free. Like I we'll send you an email with all the resources and slides and stuff like that. All right. Thank you all so much for joining and have a wonderful rest of your day or evening.
